Sankt Gallen, Univ., Diss., 2003.

Diss. Univ. St. Gallen, 2005.

Diss. Wirtschaftswiss. St. Gallen, 1988 ; Nr. 1088. / Bibliogr.: p. 309-332.

Master-Arbeit Univ. St. Gallen, 2007.

Thesis (doctoral)--Universität St. Gallen, 2006.

Universiẗat, Diss., 2005/2006--Münster.

01 Abstract: This thesis is concerned with the robust methods in portfolio theory. Different risk measures used in portfolio management are introduced and the corresponding robust portfolio optimization problems are formulated. The analytical solutions of the robust portfolio optimization problem with the lower partial moments (LPM), value-at-risk (VaR) or conditional value-at-risk (CVaR), as a risk measure, are presented. The application of the worst-case conditional value-at-risk (WCVaR) to robust portfolio management is proposed. This thesis considers WCVaR in the situation where only partial information on the underlying probability distribution is available. The minimization of WCVaR under mixture distribution uncertainty, box uncertainty, and ellipsoidal uncertainty are investigated. Several numerical examples based on real market data are presented to illustrate the proposed approaches and advantage of the robust formulation over the corresponding nominal approach.

The portfolio selection problem has been widely understood and practised for millennia, but it was rst formalised by Markowitz (1952) with the proposition of a risk-reward trade-o model. Since then, portfolio selection models have continued to evolve. The general consensus is that three objectives, to maximise the uncertain Rate Of Return (ROR), to maximise liquidity and to minimise risk, should be considered. It was found that there are opportunities for improvement within the existing portfolio selection models. This can be attributed to three gaps within the existing models. Generally, existing portfolio selection models are generic, especially in how they incorporate risk, they generally do not incorporate Socially Responsible Investing (SRI), and generally they are considered to be unvalidated. This dissertation set out to address these gaps and compare the real-world performance of generic and individualised portfolio selection models. A new method of accounting for risk was developed that consolidates the portfolio's market risk with the investor's nancial risk tolerance. Two portfolio selection models that incorporate individualised risk and SRI objectives were developed. These two models were called the risk-adjusted and social models, respectively. These individualised models were compared to an existing generic Markowitz model. These models were formulated using stochastic goal programming. A sample of 208 companies JSE Limited companies was selected and two independent datasets were extracted for these companies, a training (2010/01/01 { 2016/12/31) and testing (2017/01/01 { 2019/12/31) dataset. The models solved were in LINGO using the training dataset and tested on an unknown future by using the testing dataset. It was found that in the training period, the individualised risk-adjusted model outperformed the generic Markowitz model and the individualised social model. Furthermore, it was found that it would not be bene cial for an investor to be Socially Responsible (SR). Nevertheless, investors invest to achieve their ROR and SRI goals in the future, not in the present. Thus, it was necessary to evaluate how the portfolios selected by all three models would have performed in an unknown future. In the testing period, both the generic Markowitz model and the risk-adjusted models had dismal performance and were signi cantly outperformed by the South African market and unit trusts. Thus, these models are not useful or suitable for their intended purpose. On the contrary, the social model portfolios achieved high ROR values, were SR, and outperformed the market and the unit trusts. Thus, this model was useful and suitable for its intended purpose. The individualised social model signi cantly outperformed the other two models. Thus, it was concluded that an individualised approach that incorporates SRI outperforms a generic portfolio selection approach. Given its unparalleled performance and novel model formulation, the social model makes a contribution to the eld of portfolio selection. This dissertation also highlighted the importance of testing portfolio selection models on an unknown future and demonstrated the potentially horri c consequences of neglecting this analysis. / Dissertation (MEng (Industrial Engineering))--University of Pretoria 2021. / Industrial and Systems Engineering / MEng (Industrial Engineering) / Unrestricted

This dissertation deals with the securities portfolio optimization. After introducing the definitions, I try to explain the particular investment instruments with regard to returns and risks. The following part provides a theory which tells more about different market risks and returns on the final securities portfolio. Concerning these models the effective portfolio has been set up.

In Banken wird zunehmend das Modell von Markowitz zur Portfoliooptimierung als verkaufsförderndes Instrument verwendet. Dieses Modell stellt jedoch lediglich eine theoretische Grundlage zur Portfoliobildung dar, berücksichtigt jedoch keine Transaktionskosten oder Besonderheiten von Kleinanlegern. Es wird in die Thematik der Portfoliooptimierung eingeführt und mit Hilfe praktischer Überlegungen zur Kostenstruktur eine Modellwelt zur Ermittlung des erwartenen (Nutzen des) Endvermögens entwickelt. Dabei wird das Black-Scholes- Modell verwendet um in Simulationen Handlungsempfehlungen unter Berücksichtigung besonderes Eigenschaften von Kleinanlegern herauszuarbeiten und den Einfluss von Kosten auf das Endvermögen zu analysieren. Zur Bestimmung optimaler Portfolios kommt die Martingalmethode zur Lösung eines dynamischen Optimierungsproblems zum Einsatz.